• Proceedings of the KSME Conference
• /
• 2001.11a
• /
• pp.698-702
• /
• 2001

This paper presents a combinatorial method to compute the solutions of optimization problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The hybrid algorithm is not only faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. And the enhanced artificial life algorithm is applied to optimum design of high-speed, short journal bearings and the usefuless is verified through this example.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.529-532
• /
• 1988

This paper proposes a graph matching algorithm based on simulated annealing, which assures the globally optimal solution for circuit partitioning for the placement in the rectilinear region occurring as a result of the pre-placement of some macro cells, or onto the nonplanar surface in some military or space applications. The circuit graph ($G_{C}$) denoting the circuit topology is formed by a hierarchical bottom-up clustering of cells, while another graph called region graph ($G_{R}$) represents the geometry of a planar rectilinear region or a nonplanar surface for circuit placement. Finding the optimal many-to-one vertex mapping function from $G_{C}$ to $G_{R}$, such that the total mismatch cost between two graphs is minimal, is a combinatorial optimization problem which was solved in this work for various examples using simulated annealing.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.253-256
• /
• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• Journal of the Korea Society for Simulation
• /
• v.14 no.2
• /
• pp.25-34
• /
• 2005

Determination of component mounting sequence on printed circuit board assembly process is a typical NP-hard problem. It is a kind of traveling salesman problems, but it has one more hard to meet constraint of matching component type per mounting position as well as searching the shortest path. An efficient method is developed by separation of crowed area and allowing up to two slots per component type. A simulation model is constructed using Visual C++ for evaluation of the suggested heuristic.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.245-248
• /
• 2000

This paper proposes a cooperative parallel tabu search which incorporates with the historical information exchange among processors in addition to its own searching of each processor. We investigate the influence of our proposed cooperative parallel tabu search by comparison with a serial tabu search. We also propose two extensions of the cooperative parallel tabu search which are the cooperative construction of tabu memory and the selection of cooperative partner. Through computational experiment, we observe the improvement of solutions by our proposed method.

• Journal of KIISE:Software and Applications
• /
• v.26 no.2
• /
• pp.297-305
• /
• 1999

본 논문에서는 컴퓨터를 사용한 이진 위상 홀로그램의 설계시 요구되는 조합 최적화 문제(combinatorial optimization problem)를 유전자 알고리즘을 사용하여 해결하고자한다. 이진 위상 홀로그램의 설게는 출력 면에서 원하는 이미지를 생성하기 위하여 홀로그램의 각 셀에 이진 위상을 결정하는 것으로 최적화 문제로 귀착된다. 유전자 알고리즘을 이진 위상 홀로그램 설계에 효율적으로 적용하기 위하여 이차원 염색체 부호화 및 주기성을 고려한 교차 연산자등을 사용하면, 그 결과 홀로그램 설계시 요구되는 이차원 퓨리에 변환(Fourier transform)을 자연스럽고 효율적인 방법으로 수행할수 있다. 유전자 알고리즘을 사용하여 구한 최적의 이진 위상 배열로 공간 빛 변조기(spatial light modulator, SLM)를 이용하여 광학적으로 이미지를 재생하고, 재생된 광학 이미지는 원하는 이미지와 거의 일치함을 보인다.

• Water for future
• /
• v.29 no.4
• /
• pp.109-118
• /
• 1996

The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.

• Journal of Korea Society of Industrial Information Systems
• /
• v.2 no.1
• /
• pp.143-157
• /
• 1997

유전자 알고리즘(Genetic Algorithms)은 자연의 법칙에서 그 아이디어를 찾은 것으로 순회 방문자 문제(Traveling Salesman Problem : TSP) , 분배문제, 라우팅문제 등과 같은 전형적인 Combinatorial Optimization 문제에 적용되고 있다. 한편 이러한 유전자 알고리즘의 성능을 향상시키기 위해 알고리즘 실행과정에 적용할 수많은 이론과 경험적인 기법이 제시되고 있는데 이러한 기법들은 대부분 우수형질을 확보함으로써 최적의 값을 효과적으로 탐색하기 위한 것이다. 즉, 개체의 우수 형질 확보를 위한 부모 선택방법, 교차의 범위와 위치 및 방법, 그리고 돌연변이의 크기와 방법등이 포함된다. 본 연구에서는 자연의 법칙에서와 같이 자손 세대의 형질이 부모 세대보다 우수할 수 있음을 전제로 적응도 가중치에 의한 확률적인 방법에 의해서 선택하는 방법을 개선하여 부모세대가 같지 않게 하고, 우수형질이 유전되도록 하여 자손세대의 적응도가 부모세대보다 높도록 함으로써 최적의 값을 효과적으로 탐색할 수 있음을 실험하였다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.1
• /
• pp.15-19
• /
• 2004

Ant Colony System(ACS) is a meta heuristic approach based on biology in order to solve combinatorial optimization problem. It is based on the tracing action of real ants which accumulate pheromone on the passed path and uses as communication medium. In order to search the optimal path, ACS requires to explore various edges. In existing ACS, the local updating rule assigns the same pheromone to visited edge. In this paper, our local updating rule gives the pheromone according to the number of visiting times and the distance between visited cities. Our approach can have less local optima than existing ACS and find better solution by taking advantage of more informations during searching.

• International conference on construction engineering and project management
• /
• 2007.03a
• /
• pp.530-539
• /
• 2007

Many construction projects such as highways, pipelines, tunnels, and high-rise buildings typically contain repetitive activities. Research has shown that the Critical Path Method (CPM) is not efficient in scheduling linear construction projects that involve repetitive tasks. Linear Scheduling Method (LSM) is one of the techniques that have been developed since 1960s to handle projects with repetitive characteristics. Although LSM has been regarded as a technique that provides significant advantages over CPM in linear construction projects, it has been mainly viewed as a graphical complement to the CPM. Studies of scheduling linear construction projects with resource consideration are rare, especially with multiple resource constraints. The objective of this proposed research is to explore a resource assignment mechanism, which assigns multiple critical resources to all activities to minimize the project duration while satisfying the activities precedence relationship and resource limitations. Resources assigned to an activity are allowed to vary within a range at different stations, which is a combinatorial optimization problem in nature. A heuristic multiple resource allocation algorithm is explored to obtain a feasible initial solution. The Simulated Annealing search algorithm is then utilized to improve the initial solution for obtaining near-optimum solutions. A housing example is studied to demonstrate the resource assignment mechanism.